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Optics Express

Optics Express

  • Editor: C. Martijn de Sterke
  • Vol. 18, Iss. 25 — Dec. 6, 2010
  • pp: 26535–26549

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Three-wavelength murine photoplethysmography for estimation of vascular gold nanorod concentration

Gregory J. Michalak, Jon A. Schwartz, Glenn P. Goodrich, and D. Patrick O’Neal  »View Author Affiliations


Optics Express, Vol. 18, Issue 25, pp. 26535-26549 (2010)
http://dx.doi.org/10.1364/OE.18.026535


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Abstract

Nanoparticle-assisted photo-thermal (NAPT) ablation has become a new and attractive modality for the treatment of cancerous tumors. This therapy exploits the passive accumulation of intravenously delivered optically resonant metal nanoparticles into tumors, however, the circulating bioavailability of these particles is often unknown. We present a non-invasive optical device capable of monitoring the circulation of optically resonant gold nanorods. The device, referred to as a pulse photometer, uses the technique of multi-wavelength photoplethysmography. We simultaneously report the circulation of gold nanorods and oximetry for six hours post-injection in mice with no anesthesia and remove the probe when not collecting data. The instrument shows good agreement (R2=0.903, n=30) with ex vivo spectrophotometric analysis of blood samples. The real-time feedback provided has a strong potential for reducing variability and thus improving the efficacy of similar clinical therapies.

© 2010 OSA

1 Introduction

Optically resonant metal nanoparticles have become an increasingly popular tool in the detection and treatment of cancer. Due to their near-infrared (NIR) optical properties, these metal nanoparticles are compatible with modalities such as in vitro optical microscopy [1

S. Lal, S. E. Clare, and N. J. Halas, “Nanoshell-enabled photothermal cancer therapy: impending clinical impact,” Acc. Chem. Res. 41(12), 1842–1851 (2008). [CrossRef] [PubMed]

–3

C. Loo, A. Lowery, N. Halas, J. West, and R. Drezek, “Immunotargeted nanoshells for integrated cancer imaging and therapy,” Nano Lett. 5(4), 709–711 (2005). [CrossRef] [PubMed]

], optical coherence tomography [4

A. M. Gobin, M. H. Lee, N. J. Halas, W. D. James, R. A. Drezek, and J. L. West, “Near-infrared resonant nanoshells for combined optical imaging and photothermal cancer therapy,” Nano Lett. 7(7), 1929–1934 (2007). [CrossRef] [PubMed]

], and nanoparticle-assisted photo-thermal therapy (NAPT) of cancerous tumors [5

X. Huang, P. K. Jain, I. H. El-Sayed, and M. A. El-Sayed, “Plasmonic photothermal therapy (PPTT) using gold nanoparticles,” Lasers Med. Sci. 23(3), 217–228 (2008). [CrossRef]

–8

J. H. Park, G. von Maltzahn, M. J. Xu, V. Fogal, V. R. Kotamraju, E. Ruoslahti, S. N. Bhatia, and M. J. Sailor, “Cooperative nanomaterial system to sensitize, target, and treat tumors,” Proc. Natl. Acad. Sci. U.S.A. 107(3), 981–986 (2010). [CrossRef] [PubMed]

]. One type of metal nanoparticle widely used is the gold nanorod which can be tuned to have very high absorption cross sections in the visible and NIR wavelengths [9

H. Wang, T. B. Huff, D. A. Zweifel, W. He, P. S. Low, A. Wei, and J. X. Cheng, “ In vitro and in vivo two-photon luminescence imaging of single gold nanorods,” Proc. Natl. Acad. Sci. U.S.A. 102(44), 15752–15756 (2005). [CrossRef] [PubMed]

]. This tuning is achieved by modifying the aspect ratio of the nanorod, thus red-shifting the peak spectral attenuation concomitant with an increase in the ratio of the longitudinal to transverse dimension. These particles can therefore be used in NAPT to enhance the NIR energy absorption of an in vivo target and aid in the thermal destruction of tumor tissue.

Gold nanorods, smaller but optically similar to gold nanoshells, can be used to exploit the defective vasculature in many tumors that result from rapid metabolism and angiogenesis. This passive diffusion-like process is termed the enhanced permeability and retention effect (EPR). Also, simple surface modifications can be used to cover the surface of gold nanorods, increasing their vascular circulation half-lives from minutes to hours [10

T. Niidome, M. Yamagata, Y. Okamoto, Y. Akiyama, H. Takahashi, T. Kawano, Y. Katayama, and Y. Niidome, “PEG-modified gold nanorods with a stealth character for in vivo applications,” J. Control. Release 114(3), 343–347 (2006). [CrossRef] [PubMed]

, 11

Y. Akiyama, T. Mori, Y. Katayama, and T. Niidome, “The effects of PEG grafting level and injection dose on gold nanorod biodistribution in the tumor-bearing mice,” J. Control. Release 139(1), 81–84 (2009). [CrossRef] [PubMed]

]. This makes them available for tumor extravasation for a longer period of time increasing the efficacy of the treatment.

Currently available methods used to monitor the vascular concentration of gold nanoparticles employ invasive procedures. Furthermore, it is difficult to predict patient specific variability and immune responses to the nanoparticles. This is problematic for nanoparticle-based therapies because causality of the failure of nanoparticles to effectively accumulate in a target tissue is often unknown. Invasive monitoring of the vascular concentration of nanoparticles in a patient would involve repetitive blood sampling and costly and time consuming analytical techniques that would not provide real-time feedback and could be subject to sample contamination [12

W. D. James, L. R. Hirsch, J. L. West, P. D. O’Neal, and J. D. Payne, “Application of INAA to the build-up and clearance of gold nanoshells in clinical studies in mice,” J. Radioanal. Nucl. Chem. 271(2), 455–459 (2007). [CrossRef]

, 13

H. Xie, K. L. Gill-Sharp, and D. P. O’Neal, “Quantitative estimation of gold nanoshell concentrations in whole blood using dynamic light scattering,” Nanomedicine 3(1), 89–94 (2007). [CrossRef] [PubMed]

]. An analysis of these studies suggest, that for small animals, the large amount of blood drawn over the course of the accumulation phase relative to the total blood volume (e.g. up to 10%) may impact the characteristics of the extravasation process.

Optical methods have recently been explored as a method for monitoring the in vivo activities of gold nanoparticles [14

R. T. Zaman, P. Diagaradjane, J. C. Wang, J. Schwartz, N. Rajaram, K. L. Gill-Sharp, S. H. Cho, H. G. Rylander, J. D. Payne, S. Krishnan, and J. W. Tunnell, “ In vivo detection of gold nanoshells in tumors using diffuse optical spectroscopy,” IEEE. J. Sel. Top. Quant. Electron. 13, 1715–1720 (2007). [CrossRef]

–18

Y. Wang, X. Xie, X. Wang, G. Ku, K. L. Gill, D. P. O’Neal, G. Stoica, and L. V. Wang, “Photoacoustic tomography of a nanoshell contrast agent in the in vivo rat brain,” Nano Lett. 4(9), 1689–1692 (2004). [CrossRef]

]. This is made possible because the energy most attenuated by these nanoparticles resides in the region of wavelengths (700-1100 nm) known as the tissue optical window. It is in this band that hemoglobin, a primary absorber in vascular tissue, along with melanin and water, demonstrate extinction minima and thus in vivo penetration depth is maximal.

The spectral analysis of arterial blood has been employed in applications like oximetry [19

J. W. Severinghaus and Y. Honda, “History of blood gas analysis. VII. Pulse oximetry,” J. Clin. Monit. 3(2), 135–138 (1987). [CrossRef] [PubMed]

, 20

J. G. Webster, Design of Pulse Oximeters , Chapter 4, pp. 40–55, New York, NY, Taylor and Francis Group, 1997.

], glucosimetry [21

K. Yamakoshi and Y. Yamakoshi, “Pulse glucosimetry: a new approach for noninvasive blood glucose measurement using instantaneous differential near-infrared spectrophotometry,” J. Biomed. Opt. 11(5), 1–9 (2006). [CrossRef]

], and pulse dye densitometry [22

T. Iijima, T. Aoyagi, Y. Iwao, J. Masuda, M. Fuse, N. Kobayashi, and H. Sankawa, “Cardiac output and circulating blood volume analysis by pulse dye-densitometry,” J. Clin. Monit. 13(2), 81–89 (1997). [CrossRef] [PubMed]

–24

N. Taguchi, S. Nakagawa, K. Miyasaka, M. Fuse, and T. Aoyagi, “Cardiac output measurement by pulse dye densitometry using three wavelengths,” Pediatr. Crit. Care Med. 5(4), 343–350 (2004). [CrossRef] [PubMed]

]. These methods isolate the time-varying attenuation of light resulting from the arterial pulsation of each heartbeat. A photodetector circuit is used to detect the amount of transmitted light at selected wavelengths by converting it to a time varying electrical signal. This signal is a waveform referred to as a photoplethysmogram (PPG) which consists of a time varying portion (AC) and baseline (DC). The magnitude of the AC signal is the envelope of the PPG and the magnitude of the DC portion is the average value of the PPG. This allows for an analysis of the isolated optical properties of arterial blood, which change, often drastically, with the addition of optically attenuating agents. Pulse dye densitometry exploits the same phenomena to measure the concentration of a dye injected into the vasculature suggesting that similar techniques could be applied to the monitoring of optically extinguishing nanoparticles.

The measurement of optically attenuating species in blood can be done by employing the Beer-Lambert Law at several wavelengths. By examining the ratio of the changes in attenuation of light at these wavelengths, the calculations become path-length independent. This suggests, in theory, that the measurements are also independent of anatomical probing location as long as a suitable pulsatile signal is obtained. In pulse oximetry, for example, the ratio of pulsatile changes at a red (λ1) and infrared wavelength (λ2) is used to determine the percent oxygen saturation (SpO2) in arterial blood. These measurements can be made on several anatomical locations including the fingers, toes, earlobes, and noses with little difference in the measured oxygen saturation. The ratio of these pulsatile changes can be determined using the DC and AC portions of the PPG, which can be equated to small changes in attenuation of light referred to as ΔA. The ratio of ΔA’s at two wavelengths is often referred to as R [20

J. G. Webster, Design of Pulse Oximeters , Chapter 4, pp. 40–55, New York, NY, Taylor and Francis Group, 1997.

] as defined in Eq. (1).

R= Δ A λ1 Δ A λ2= log ( DC DC−AC) λ1 log ( DC DC−AC) λ2~ ( AC DC) λ1 ( AC DC) λ2.
(1)

The addition of multiple wavelengths to determine several ratios can be used to determine the concentrations of several optically attenuating species in the arterial blood [25

Y. Mendelson, R. M. Lewinsky, and Y. Wasserman, “Multi-wavelength reflectance pulse oximetry,” Anesth. Analg. 94(1 Suppl), S26–S30 (2002). [PubMed]

–27

J. Kraitl, H. Ewald, and H. Gehring, “An optical device to measure blood components by a photoplethysmographic method,” J. Opt. A, Pure Appl. Opt. 7(6), S318–S324 (2005). [CrossRef]

]. This multi-wavelength technique has recently been employed in the improvement of the pulse oximeter to account for the contribution of pulsatile tissue, venous blood, dyshemoglobins, and total hemoglobin concentration [28

S. J. Barker, J. Curry, D. Redford, and S. Morgan, “Measurement of carboxyhemoglobin and methemoglobin by pulse oximetry: a human volunteer study,” Anesthesiology 105(5), 892–897 (2006). [CrossRef] [PubMed]

].

We present a three-wavelength pulse photometer capable of determining the concentration of gold nanorods, reported in units of optical density, in the arterial blood of a murine model. The animal model used generates a very small distension of the arteries/arterioles which in turn generates a very small optical pulsatile signal. While this inherent disadvantage is mitigated to some extent in larger mammals and humans, the murine model is common in pre-clinical drug testing. In addition, a formal evaluation of the in vivo performance of manufactured batches of nanoparticles such as nanorods is often employed as a final metric of quality control and to define the circulating characteristics of a specific batch. We also explore the feasibility of concurrent oximetry measurements, highlighting the potential expanded utility of this device in a clinical setting.

2 Materials and methods

2.1 Institutional animal care and use approval

Female BALB/c mice were used in testing the pulse photometer. Anesthesia delivery and animal handling protocols used for testing at Louisiana Tech University were approved by the institutional animal care and use committee (IACUC). Additional experiments were performed at Nanospectra Biosciences, Inc. in Houston, TX without anesthesia. The animals were measured with the pulse photometer during manual restraint, a procedure independently approved by Nanospectra’s IACUC.

2.2 Instrumentation

Custom designed plastic clips for pulse oximetry compatible with mouse anatomy were purchased from Starr Life Sciences [Starr Life Sciences (Oakmont, Pennsylvania) 741 Tail sensor clip]. These clips are produced having a centrally located channel-depression to securely accommodate a mouse’s tail or foot without applying excessive pressure and reduce ambient light exposure. Several clips were purchased and modified by the addition of a photodiode (Hamamatsu S1337-33BR) and four-wavelength LED [Marubeni (Santa Clara, California) L660/735/805/940-40B42]. These LED’s are stock item opto-electronic components that contain wavelengths of 660 nm, 735 nm, 805 nm, and 940 nm. Our three-wavelength measurements employed the 805 nm LED to match the maximum extinction peak of the nanorods, as well as the 660 nm and 940 nm emitting elements.

The circuitry of the pulse photometer is designed to accompany eight data collection channels. This is done by using CMOS logic circuitry to count through eight channels and synchronize sample-and-hold chips with the LED emission at each wavelength. The timing element is a multivibrator chip (CD4047BCN) configured in an astable free running mode producing pulses at a rate of 1.19 kHz and driving a 3-bit counter (MM74HC393N). This is connected to a 3-to-8 decoder (MM74HC138N) separating pulses amongst eight different channels, each having pulse repetition rates of ≈150 Hz with <15% duty cycle. This is adequate to collect the PPG of a mouse (typically less than 600 beats/min, or 10 Hz). These pulses are inverted (MM74HC04N) and used to control four sample-and-hold circuits. This permitted the addition of a channel specifically used to detect ambient light while no wavelengths are emitted and subtract it from the signals collected during the emission of each wavelength. The signals from the sample-and-hold chips are then fed through a first-order analog filter (Fc ≈28 Hz) for smoothing and attenuation of power line interference and then collected with a National Instruments DAQ (USB-6008) set to 10,000 samples/sec. The pulses from the decoder are sent to buffers (LM324N) to supply power to the LED’s. The buffers are connected in series with the LED’s by variable resistors allowing the user to adjust the power of each source to obtain maximal light penetration at each wavelength without saturating the detector. The LED package is configured having a common anode and separate cathodes for each wavelength. The anode is biased with the 5 volt supply used to drive the logic circuitry. The signals from the decoder are therefore inverted in order to synchronize the sampling of one channel with the emission of its corresponding wavelength.

The circuitry is soldered to a printed circuit board (ExpressPCB) designed using computer-aided-design software. Integrated circuit mounts were soldered to the board to provide easy insertion and removal of the IC chips. The board was then mounted inside of a 6” x 4” x 2” plastic encasing to help protect the circuitry. 15-pin connectors were mounted in the casing for the power, probe, and data output connections. This allowed for easy swapping of probes and connection and disconnection of the power and data lines.

The data acquisition card collects the data from the circuitry and imports it into LabVIEW in 1 second waveforms on separate channels for analysis. Our LabVIEW program first subtracts the signal from the ambient light channel from the signals at each wavelength. These are then separated into their AC and DC portions using standard LabVIEW VI’s. A third order Butterworth bandpass filter (4-10 Hz passband corresponding to typical murine heart rates between 240 and 600 bpm) is used to condition the AC signals and remove unwanted frequencies. These values are used to determine SpO2 and nanorod optical density. A schematic diagram of the entire optical system coupled to the tail of an animal along with a graphical description of the measurement of pulsatile signals due to arterial blood can be seen in Fig. 1 .

Fig. 1 – Schematic of the optical pulse photometer coupled to an animal and diagram of the examined pulsatile arterial blood.

2.3 Optical properties of gold nanorods

PEG-conjugated gold nanorods were obtained from Nanospectra Biosciences, Inc. Their visible/infrared extinction spectrum was measured using spectrophotometry. A 1% dilution of the nanorods was prepared and scanned in our spectrophotometer [Beckman Coulter (Brea, California) DU 800]. A normalized spectrum of the nanorods with the emission spectra from the LED’s can be seen in Fig. 2 .

Fig. 2 - Normalized extinction spectrum of the gold nanorods (grey line) with overlaid spectra from the LED’s showing the preferential attenuation at 805 nm compared to 660 and 940 nm.

The stock nanorods had an optical density of 68.3 at 805 nm and optical densities of 24.1 and 13.8 at 660 nm and 940 nm respectively. The ratios of the optical densities were used in the algebraic equations used to determine the optical density of the nanorods and SpO2 in whole blood.

2.4 Spectrophotometric analysis of blood draws

As previously described, we collected blood samples at time points selected for comparison to pulse photometer measurements [16

G. J. Michalak, G. P. Goodrich, J. A. Schwartz, W. D. James, and D. P. O’Neal, “Murine photoplethysmography for in vivo estimation of vascular gold nanoshell concentration,” J. Biomed. Opt. 15(4), 047007 (2010). [CrossRef] [PubMed]

]. This simple UV-VIS assay consists of diluting 5 µL of blood extracted from the tail vein into 95 µL of a 10% Triton-X solution to lyse scattering confounders such as red blood cells. The extinction of the nanorods, after subtraction of the hemoglobin baseline, is then directly quantified. The blood samples were processed in micro-cuvettes [Brandtech (Essex, Connecticut) Ultra-Micro] in our low-volume spectrophotometer. The average value of oxyhemoglobin in the 30 samples (described below in section 2.6 and reported in section 3.1) was 0.1320 ± 0.0075 mM as measured using the extinction of each sample at 560 nm. This corresponds to 17.0280 ± 0.0484 g/dL in whole blood after accounting for dilution. The small variation in oxyhemoglobin concentration seen here suggests acceptable experimental error in the collection of the blood samples using a 10 µL pipette. The measured nanorod optical densities in the samples ranged from 0.0167 to 0.2207 at 805 nm which corresponds to a 0.3340-4.4140 optical density in whole blood. These values are well above the RMS noise of our spectrophotometer which was specified as 0.0002 absorbance units at 500 nm. The previous report compared this UV-VIS technique to an instrumental neutron activation analysis-based assay which produced a model (R2 = 0.98) in which all points fell within the 95% prediction interval [16

G. J. Michalak, G. P. Goodrich, J. A. Schwartz, W. D. James, and D. P. O’Neal, “Murine photoplethysmography for in vivo estimation of vascular gold nanoshell concentration,” J. Biomed. Opt. 15(4), 047007 (2010). [CrossRef] [PubMed]

].

2.5 Estimation of the attenuation coefficients of oxygenated and reduced whole blood

The optical density changes caused by the pulsation of blood are different depending on the interrogation wavelength. These changes are due to the optical attenuation coefficients of individual components of whole blood. In a simplified model, these are oxygenated and reduced whole blood. In the case when optically active nanoparticles are introduced to the circulating blood, there will also be a contribution from their optical attenuation. The optical properties of whole blood have been measured at several wavelengths in previous experiments [29

W. G. Zijlstra, A. Buursma, and W. P. Meeuwsen-van der Roest, “Absorption spectra of human fetal and adult oxyhemoglobin, de-oxyhemoglobin, carboxyhemoglobin, and methemoglobin,” Clin. Chem. 37(9), 1633–1638 (1991). [PubMed]

–32

D. J. Faber, M. C. G. Aalders, E. G. Mik, B. A. Hooper, M. J. C. van Gemert, and T. G. van Leeuwen, “Oxygen saturation-dependant absorption and scattering of blood,” Phys. Rev. Lett. 93(2), 1–4 (2004). [CrossRef]

]. Since many of these experiments were performed ex vivo, we turned to the empirical estimation of the optical properties for reduced and whole blood. This was achieved using three techniques:

  • 1. In vivo estimation of the effective attenuation coefficient of oxygenated whole blood by inducing 100% SpO2 and intravenous injection of gold nanorods in mice.
  • 2. Obtaining the optical properties of reduced whole blood from the literature and determining the effective attenuation coefficients.
  • 3. Adjusting the optical properties of reduced whole blood by referring to a calibration curve used in standard pulse oximetry.

2.5.1 Oxygenated whole blood optical properties

The attenuation properties of fully oxygenated blood were quantified in vivo by controlling blood oxygenation in five female 18-20 g BALB/c mice. The mice were anesthetized with isoflurane vaporized [Dentry Biomedical, Incorporated (Hunt Valley, Maryland) Isoflurane Vaporizer] with 95% oxygen delivered at 1 L/min with an oxygen concentrator [Invacare 5 (Elyria, Ohio)]. This theoretically set their blood oxygenation to a stable level between 97 and 100% [33

A. C. Guyton, and J. E. Hall, Textbook of Medical Physiology , Chapters 39–40, pp. 491–513, (Philadelphia, PA, Elsevier Saunders, 2006).

]. A catheter inserted into the tail vein allowed for controlled infusion of nanoparticles. Their core temperature was also maintained at approximately 40 °C using a temperature controlled heating pad [Physitemp (Clifton, New Jersey) TCAT-2LV Controller] in order to induce vasodilation. The pulse photometer was then attached to the foot and signal quality was assessed using the pulse amplitude and standard deviation over thirty second periods. A stable PPG with acceptable magnitude was characterized by a standard deviation of R 805/940 over the thirty seconds of less than 0.02 and an average AC magnitude > 5 mVp-p. Once signal stability was achieved, injections of nanorods were then delivered at the same dose as typical nanoshell injections (4.5 μl/g). The ΔR using the ratio of ΔA’s at 805 and 940 nm was measured and recorded. Once this value had stabilized, again assessed by pulse amplitude and standard deviation, this value was recorded and a 5 μL blood draw was then taken, processed, and analyzed using spectrophotometry to determine the optical density of the nanorods in the circulating blood at 805 nm.

The attenuation coefficients of oxygenated whole blood at the three wavelengths were determined by using the measured nanorod optical density in each of the five mice. We describe the contribution of nanorods in terms of optical density and the contribution of hemoglobin as the attenuation coefficient. Since the optical density of the nanorods is that of a solution having a path length of 1 cm, the terms for nanorods and hemoglobin can be added algebraically. Manipulation of Beer’s law for 805 and 940 nm yields Eq.’s 2a-2d.

R 805/940= 0.8 μ Hb O2 940+ μ NR 805 μ Hb O2 940+0.2018 μ NR 805,
(2a)
μ Hb O2 805=0.8 μ Hb O2 940,
(2b)
μ Hb O2 660=0.5 μ Hb O2 940,
(2c)
μ NR 940=0.2018 μ NR 805.
(2d)

In these equations,, μ Hb O2 805, and μ Hb O2 940 are the effective attenuation coefficients of oxygenated whole blood at 660, 805, and 940 nm respectively. The effective attenuation accounts for both the absorption and scattering of light which is dependent on the hematocrit, which is assumed to be constant for each measurement. μ NR 805is the optical density of the nanorods at 805 nm as measured by spectrophotometry. The denominator of the first equation contains the term 0.2018 μ NR 805because the ratio of the extinctions of the nanorods at 940 nm and 805 nm was 0.2018. Therefore, it was assumed that this ratio also was maintained when the nanorods were detected with the pulse photometer. The effective attenuation coefficient of oxygenated whole blood at 805 nm was approximated by μ Hb O2 805=0.8 μ Hb O2 940since R 805/940 was measured as ≈0.8, seen previously using pulse photometry during oxygen delivery. The effective attenuation coefficient of oxygenated whole blood at 660 nm was approximated as μ Hb O2 660=0.5 μ Hb O2 940by using an empirical calibration curve given by Webster [20

J. G. Webster, Design of Pulse Oximeters , Chapter 4, pp. 40–55, New York, NY, Taylor and Francis Group, 1997.

]. This calibration curve reported that the ratio of ΔA’s at 660 and 940 nm, R 660/940, was approximately 0.5 when SpO2 was equal to 100%. The estimates of μ Hb O2 660, μ Hb O2 805, and μ Hb O2 940for each of five mice were averaged and are shown in Table 1 .

Table 1  - Calculated effective attenuation coefficients of oxygenated whole blood from the five mice.
          Mouse μ Hb O2 660 (cm−1) μ Hb O2 805 (cm−1) μ Hb O2 940 (cm−1)
12.05193.28304.1038
21.59352.54963.1871
31.23561.97702.4712
42.03823.26114.0764
52.30563.68894.6112
Average1.84502.95193.6899
Standard Deviation0.42630.68200.8526

2.5.2 Reduced whole blood optical properties with calibration

In order to calculate SpO2 as well as nanoparticle concentration, the attenuation coefficients of reduced whole blood needed to be approximated. Measuring fully reduced whole blood in vivo was not possible. Therefore, approximations of the optical properties of reduced whole blood were obtained from the literature. Furthermore, reduced whole blood also contains both absorbing and scattering components. Values for the absorption and scattering coefficients were therefore obtained and used to determine the attenuation coefficients at the three wavelengths used in the pulse photometer measurements.

The molar absorption coefficients of reduced hemoglobin were first obtained from Prahl [34

S. A. Prahl, “Tabulated Molar Extinction Coefficients of Reduced and Oxygenated Hemoglobin,” http://omlc.ogi.edu/spectra/hemoglobin/summary.html (1998)

]. A typical hemoglobin concentration value of 2.303 mM was used to then determine the absorption coefficient of reduced whole blood. Next, the scattering coefficients and anisotropy of reduced whole blood were estimated using spectral data from a previous report [32

D. J. Faber, M. C. G. Aalders, E. G. Mik, B. A. Hooper, M. J. C. van Gemert, and T. G. van Leeuwen, “Oxygen saturation-dependant absorption and scattering of blood,” Phys. Rev. Lett. 93(2), 1–4 (2004). [CrossRef]

]. The effective attenuation coefficients, μ effλ, at 660, 805, and 940 nm were then calculated using Eq. (3) obtained from Welch and van Gemert [35

A. J. Welch, and M. J. C. van Gemert, Optical-Thermal Response of Laser-Irradiated Tissue , New York, NY, Plenum Press, 1995.

] defining the effective attenuation coefficient in dense scattering biological media.
μ effλ= 3( μ a Hbrλ)( μ a Hbrλ+(1−g) μ s Hbrλ).
(3)
μ a Hbrλand μ s Hbrλ are the absorption and scattering coefficients, respectively, of reduced whole blood and g is the anisotropy at the wavelengths used in the pulse photometer. The anisotropy, which describes the relative degree of forward scattering, can be defined as the cosine of the mean scattering angle. Blood is a primarily forward scattering medium with a measured anisotropy of >0.99 at the wavelengths of interest [32

D. J. Faber, M. C. G. Aalders, E. G. Mik, B. A. Hooper, M. J. C. van Gemert, and T. G. van Leeuwen, “Oxygen saturation-dependant absorption and scattering of blood,” Phys. Rev. Lett. 93(2), 1–4 (2004). [CrossRef]

]. The reduced scattering coefficient, μ s Hbr', which is defined as (1−g) μ s Hbrλ, quantifies the attenuation of light due to scattering. These calculated values were then adjusted by referring to the calibration curve for SpO2 with respect to R 660/940 given in Webster. This calibration curve can be seen in Fig. 3 .

Fig. 3 - Calibration curve showing the linear correlation between R 660/940 and SpO2 (SpO2 = −36.589R 660/940 + 117.15, R2 = 0.9931).

Beer’s law was used to determine the empirical attenuation coefficients of reduced blood by using R 660/940 at 6 different oxygen saturation percentages and the previously calculated attenuation coefficients of oxygenated whole blood. This is shown in Eqs. (4a-4c).
R 660/940= S( μ Hb O2 660)+(1−S)( μ H br 660) S( μ Hb O2 940)+(1−S)(0.2404 μ H br 660),
(4a)
μ H br 940=0.2404 μ H br 660,
(4b)
μ H br 805=0.2540 μ H br 660.
(4c)
μ Hb O2 660is the attenuation coefficient of oxygenated whole blood found previously and S is the oxygen saturation given as a fraction (0-1) at a particular value of R 660/940 given by the calibration curve. μ H br 660, μ H br 805, and μ H br 940 are the effective attenuation coefficients of reduced whole blood. 0.2404 μ H br 660 and 0.2540 μ H br 660 were used as μ H br 940and μ H br 940 respectively in order to keep the ratios of the attenuation coefficients the same as those calculated using the literature. The 6 calculated values for μ H br 660, μ H br 805, and μ H br 940 were then averaged to obtain the attenuation coefficients used to estimate the nanorod optical density and SpO2 in subsequent experiments. The optical properties of reduced whole blood from both the literature and after adjustment can be seen in Table 2 and Table 3 respectively.

Table 2  - Optical properties of reduced whole blood obtained from the literature [32

D. J. Faber, M. C. G. Aalders, E. G. Mik, B. A. Hooper, M. J. C. van Gemert, and T. G. van Leeuwen, “Oxygen saturation-dependant absorption and scattering of blood,” Phys. Rev. Lett. 93(2), 1–4 (2004). [CrossRef]

,34

S. A. Prahl, “Tabulated Molar Extinction Coefficients of Reduced and Oxygenated Hemoglobin,” http://omlc.ogi.edu/spectra/hemoglobin/summary.html (1998)

].
Wavelength μ a Hbr (cm−1) μ s Hbr (cm−1) g μ s Hbr' (cm−1) μ ef f Hbr (cm−1)
66017.28093180.99501.590031.2781
8053.92952350.99391.42417.9442
9403.71391830.99261.36157.5199
Table 3  – Calculated effective attenuation coefficients of reduced whole blood.
SpO2 (%) R 660/940 μ H br 660 (cm−1) μ H br 805 (cm−1) μ H br 940 (cm−1)
950.68.18692.07951.9681
900.77.98202.02741.9189
850.910.67662.71192.5667
8019.71632.46792.3358
751.1510.02092.54532.4090
701.39.94362.52572.3904
Average-9.42102.39302.2648
S. D.-1.08540.27570.2609

The average values for the effective attenuation coefficients were used in Eqs. (5a) and (5b) to solve for the nanorod optical density and SpO2.

R 805/940= S( μ Hb O2 805)+(1−S)( μ H br 805)+ μ NR S( μ Hb O2 940)+(1−S)( μ H br 940)+0.2018 μ NR,
(5a)
R 660/940= S( μ Hb O2 660)+(1−S)( μ H br 660)+0.3523 μ NR S( μ Hb O2 940)+(1−S)( μ H br 940)+0.2018 μ NR.
(5b)

A simultaneous equation solver was added to the pulse photometer LabVIEW program which calculates the SpO2 and nanorod optical density using average values of R 660/940 and R 805/940 as specified by the user.

2.6 Off-Site mouse experiments

The pulse photometer was tested at Nanospectra Biosciences, Inc. using five female BALB/c mice similar in size to those used previously monitored without the use of anesthesia to achieve two primary goals: (1) establish utility in a less controlled environment by demonstrating that the pulse photometer would work outside the production laboratory in a set of experiments performed on a single day, such as might be conducted for a nanoparticle production batch test, and (2) test its utility on a conscious subject at a convenient anatomical probing location to determine if it could be used in a clinical setting where anesthesia was not approved for a NAPT. Each mouse was injected intravenously with the standard dose of gold nanorods (4.5 μL/g) from the same batch used to determine the optical properties of whole blood and then monitored for six hours. The pulse photometer was used to probe the tail arteries to obtain estimates of nanorod optical density and oxygen saturation immediately after injection and approximately 1, 2, 3, 4, and 6 hours after injection. During each measurement, the mouse was manually restrained by the collar, and the nose was placed in an oxygen mask attached to our oxygen concentrator delivering 95% oxygen at 2 L/min to stabilize the arterial oxygen saturation. The pulse photometer probe was placed on the tail and situated such that the arteries were between the LED’s and the photodetector. It was then allowed to collect data in one-second waveforms which were averaged every five seconds. The five-second average was deemed acceptable once the following criteria were met:

  • • The five second average of both R 805/940 and R 660/940 must have had a standard deviation below 0.02.
  • • The AC amplitude of the bandpass filtered signals at each wavelength must have consistently had a value of > 5 mVp-p.
  • • The theoretically calculated oxygen saturation for the five-second average must have been at least 85%.

After each measurement, a 5 μL blood sample was obtained from the tail and analyzed using spectrophotometry. This was done to access the accuracy of the pulse photometer in determining the optical density of the nanorods in the whole blood.

3 Results

3.1 Estimates of nanorod optical density

The correlation between the estimates of the optical density of the nanorods using pulse photometry and spectrophotometry was assessed by developing a linear model. The strong correlation between the estimates can be seen in Fig. 4 . This is evident by the goodness of fit and slope near unity and non-significant y-intercept.

Fig. 4 - Linear model showing agreement between nanorod optical density measured with pulse photometry and spectrophotometry (y = 1.1566x – 0.0497, p = 6.45 x 10−16, R2 = 0.903, n = 30). The 95% confidence (large dashes) and prediction (small dashes) intervals are shown for the entire range of measured optical densities using the pulse photometer.

Of particular interest is the one data point that is outside of the 95% prediction interval. A linear model (data not shown) was produced after deletion of this point and showed significant increase in the goodness of fit (y = 1.1545x – 0.0925, p < 2 x 10−16, R2 = 0.940). This suggests that this measurement was most likely an outlier which resulted from an erroneous measurement made by the device.

A Bland-Altman analysis was conducted to assess the agreement between the calculated optical density of the nanorods in whole blood using spectrophotometry and the pulse photometer. The analysis reported a bias of −0.2244 cm−1, which is the average difference between measurements, and a precision of 0.8643 cm−1, which is equal to two standard deviations of the differences between measurements. This can be seen in Fig. 4.

Fig. 5 - Differences between the measurements made with the pulse photometer (PP) and spectrophotometry (UV/Vis) plotted with respect to the average of the two measurements with the bias (solid line) and precision (dashed lines) shown.

The low bias suggests a slight underestimation of the optical density when using the pulse photometer. This is a considerable improvement compared to the bias (−1.795 OD) reported tracking gold nanoshells using an earlier prototype [17

G. J. Michalak, H. A. Anderson, and D. P. O’Neal, “Feasibility of using a two-wavelength photometer to estimate the concentration of circulating near-infrared extinguishing nanoparticles,” J Biomed. Nanotechnol. 6(1), 73–81 (2010). [CrossRef] [PubMed]

]. However, it is evident that this underestimation is higher at large optical densities and minimal at low optical densities. The standard deviation of the differences in measurements is 0.4321, which is low when compared to the range of optical densities that were measured in the experiments (approximately 0.3-4.5).

3.2 Estimation of blood oxygen saturation

Estimates of SpO2 were obtained during each measurement. Since the mice were fed a steady flow of 95% oxygen during each measurement, we expected to measure oxygen saturations at or above 85% with minimal fluctuation; however, no attempt to validate our theoretical calculations was made. The average estimate of SpO2 was 90.87 ± 2.21%. This value is lower than expected based on prior testing of the pulse photometer as a pulse oximeter. These tests indicated that a value of approximately 96% oxygen saturation was expected [36

G. J. Michalak, “In vivo non-invasive monitoring of optically resonant metal nanoparticles using multi-wavelength photoplethysmography,” Dissertation published August 2010.

]. However, these estimates could not be validated by any other ex vivo technique such as co-oximetry or blood gas analysis due to the lack of availability of such equipment. The average measured SpO2 is not a value that would suggest severe hypoxia, often commonly measured during excessive motion, and does not have a large standard deviation suggesting that the measurement of SpO2 concurrent with the nanorod optical density is feasible in future design iterations.

4 Conclusions

We have demonstrated the use of multi-wavelength photoplethysmography for monitoring the vascular concentration of gold nanorods. Our linear model and Bland-Altman analysis revealed that the comparison of the estimates of optical density of gold nanorods in whole arterial blood using our pulse photometer and using ex vivo spectrophotometry of processed blood samples showed good agreement. The linear model showed a slope near unity with non-significant y-intercept suggesting that the pulse photometer can reproducibly monitor the circulation of gold nanorods across in vivo optical densities ranging from approximately 0.3 to 4.5. The Bland-Altman analysis showed small bias and good precision further suggesting the accuracy of the pulse photometer. Our experiments were performed over six-hour periods on murine subjects demonstrating two significant aspects of our device: (1) it is removable and can be used to monitor the circulation of nanoparticles having variable circulation half-lives, which suggests that this technology could be applicable to a wide range of optically active nanoparticles, and (2) this pulse photometer is compatible with murine anatomy and can be used without employing anesthesia. The latter is important because batch testing of nanoparticles is often performed on small subjects such as mice to minimize the injection volume. Furthermore, the use of anesthesia is often restricted and could potentially affect the circulation time of the nanoparticles. The ability to monitor the animals with anesthesia or with only manual restraint demonstrates that acceptable multi-wavelength PPGs can be obtained and used to determine the optical properties of arterial whole blood in vivo. The ability to measure PPGs at multiple anatomical sites demonstrates the ruggedness and versatility of our instrument.

The need to collect and identify an accurate PPG presents a challenge when using this technique with a murine subject. A pilot study with the pulse photometer conducted before the outset of this report examined measurements made on the foot using isoflurane anesthesia to minimize motion artifacts [36

G. J. Michalak, “In vivo non-invasive monitoring of optically resonant metal nanoparticles using multi-wavelength photoplethysmography,” Dissertation published August 2010.

]. These measurements, when correlated to blood draws in five animals (y = 1.3036x - 0.0781, p = 1.62 x 10-13, R2 = 0.954, n = 20), compare favorably to the experiments conducted without anesthesia described in this report. However, this improvement was negligible after the elimination of the influential data point. The outlier may point to a greater potential for erroneous measurements when only manual restraint is used. The potential for rare erroneous measurements stresses the need to develop additional strategies to identify motion-based errors, such as collecting multiple measurements at each time point, and also advises that the most reliable protocol for using the current prototype is to employ anesthesia in murine models when possible.

Several sources of potential error in the measurement of nanorod optical density and SpO2 were identified. The first, as mentioned previously, is that the measurement of the PPG in a 20g murine subject has been historically difficult. The signal results from a very small transient change in optical density, and collecting measurements during manual restraint presents the potential for motion artifacts. The small subject also exasperates potential variability in probe coupling each time it is reattached. The second source of error may have been related to the optical properties of the nanorods used in our experiments. For our in vivo estimates, it was assumed that the ratio of the attenuation coefficients at each wavelength used by our pulse photometer remained the same regardless of the concentration. This may not have been true, especially at high concentrations due to the effects of multiple scattering. This is suggested from the underestimation of the nanorod optical density by the pulse photometer at high concentrations and artificially low theoretical estimates of SpO2. This suggests broadening of the extinction spectrum of the nanorods at high concentrations, especially in the red band of the visible spectrum, mimicking desaturation of hemoglobin and causing these errors.

This report demonstrates that non-invasive pulse photometer technology has the potential to provide real-time monitoring of optically-active in vivo nanoparticles. With the goal of reducing the variability and increasing the efficacy of clinical therapies such as NAPT, we will refine and validate SpO2 calculations in future prototypes, and further expand its utility by monitoring nanoparticles in tumor bearing animals to determine the relationship between bioavailability and tumor extravasation. We also plan to use this device in conjunction with ongoing pre-clinical trials employing larger mammals in the near future.

Acknowledgements

The authors would like to gratefully acknowledge several individuals who assisted with this work. Pratik Adhikari, a graduate student at Louisiana Tech Biomedical Engineering, and Kelly Sharp, the Animal Program Manager at Nanospectra Biosciences, advised and assisted with animal handling and data collection during the experiments in Houston. We also wish to thank Dr. Elysse Orchard of Louisiana State University Health Sciences Center at Shreveport, LA for instruction and the loan of the isoflurane vaporizer used in our experiments at Louisiana Tech. This work was funded by a grant from the Louisiana Board of Regents Industrial Ties Research Subprogram [LEQSF(2009-12)-RD-B-07].

References and links

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S. Lal, S. E. Clare, and N. J. Halas, “Nanoshell-enabled photothermal cancer therapy: impending clinical impact,” Acc. Chem. Res. 41(12), 1842–1851 (2008). [CrossRef] [PubMed]

2.

M. P. Melancon, W. Lu, Z. Yang, R. Zhang, Z. Cheng, A. M. Elliot, J. Stafford, T. Olsen, J. Z. Zhang, and C. Li, “ In vitro and in vivo targeting of hollow gold nanoshells directed at epidermal growth factor receptor for photo thermal therapy,” Mol. Cancer Ther. 7(6), 1730–1739 (2008). [CrossRef] [PubMed]

3.

C. Loo, A. Lowery, N. Halas, J. West, and R. Drezek, “Immunotargeted nanoshells for integrated cancer imaging and therapy,” Nano Lett. 5(4), 709–711 (2005). [CrossRef] [PubMed]

4.

A. M. Gobin, M. H. Lee, N. J. Halas, W. D. James, R. A. Drezek, and J. L. West, “Near-infrared resonant nanoshells for combined optical imaging and photothermal cancer therapy,” Nano Lett. 7(7), 1929–1934 (2007). [CrossRef] [PubMed]

5.

X. Huang, P. K. Jain, I. H. El-Sayed, and M. A. El-Sayed, “Plasmonic photothermal therapy (PPTT) using gold nanoparticles,” Lasers Med. Sci. 23(3), 217–228 (2008). [CrossRef]

6.

H. Liu, D. Chen, F. Tang, G. Du, L. Li, X. Meng, W. Liang, Y. Zhang, X. Teng, and Y. Li, “Photo thermal therapy of Lewis lung carcinoma in mice using gold nanoshells on carboxylated polystyrene spheres,” Nanotechnology 19(34), 1–7 (2008). [CrossRef]

7.

D. P. O’Neal, L. R. Hirsch, N. J. Halas, J. D. Payne, and J. L. West, “Photo-thermal tumor ablation in mice using near infrared-absorbing nanoparticles,” Cancer Lett. 209(2), 171–176 (2004). [CrossRef] [PubMed]

8.

J. H. Park, G. von Maltzahn, M. J. Xu, V. Fogal, V. R. Kotamraju, E. Ruoslahti, S. N. Bhatia, and M. J. Sailor, “Cooperative nanomaterial system to sensitize, target, and treat tumors,” Proc. Natl. Acad. Sci. U.S.A. 107(3), 981–986 (2010). [CrossRef] [PubMed]

9.

H. Wang, T. B. Huff, D. A. Zweifel, W. He, P. S. Low, A. Wei, and J. X. Cheng, “ In vitro and in vivo two-photon luminescence imaging of single gold nanorods,” Proc. Natl. Acad. Sci. U.S.A. 102(44), 15752–15756 (2005). [CrossRef] [PubMed]

10.

T. Niidome, M. Yamagata, Y. Okamoto, Y. Akiyama, H. Takahashi, T. Kawano, Y. Katayama, and Y. Niidome, “PEG-modified gold nanorods with a stealth character for in vivo applications,” J. Control. Release 114(3), 343–347 (2006). [CrossRef] [PubMed]

11.

Y. Akiyama, T. Mori, Y. Katayama, and T. Niidome, “The effects of PEG grafting level and injection dose on gold nanorod biodistribution in the tumor-bearing mice,” J. Control. Release 139(1), 81–84 (2009). [CrossRef] [PubMed]

12.

W. D. James, L. R. Hirsch, J. L. West, P. D. O’Neal, and J. D. Payne, “Application of INAA to the build-up and clearance of gold nanoshells in clinical studies in mice,” J. Radioanal. Nucl. Chem. 271(2), 455–459 (2007). [CrossRef]

13.

H. Xie, K. L. Gill-Sharp, and D. P. O’Neal, “Quantitative estimation of gold nanoshell concentrations in whole blood using dynamic light scattering,” Nanomedicine 3(1), 89–94 (2007). [CrossRef] [PubMed]

14.

R. T. Zaman, P. Diagaradjane, J. C. Wang, J. Schwartz, N. Rajaram, K. L. Gill-Sharp, S. H. Cho, H. G. Rylander, J. D. Payne, S. Krishnan, and J. W. Tunnell, “ In vivo detection of gold nanoshells in tumors using diffuse optical spectroscopy,” IEEE. J. Sel. Top. Quant. Electron. 13, 1715–1720 (2007). [CrossRef]

15.

T. Niidome, Y. Akiyama, K. Shimoda, T. Kawano, T. Mori, Y. Katayama, and Y. Niidome, “ In vivo monitoring of intravenously injected gold nanorods using near-infrared light,” Small 4(7), 1001–1007 (2008). [CrossRef] [PubMed]

16.

G. J. Michalak, G. P. Goodrich, J. A. Schwartz, W. D. James, and D. P. O’Neal, “Murine photoplethysmography for in vivo estimation of vascular gold nanoshell concentration,” J. Biomed. Opt. 15(4), 047007 (2010). [CrossRef] [PubMed]

17.

G. J. Michalak, H. A. Anderson, and D. P. O’Neal, “Feasibility of using a two-wavelength photometer to estimate the concentration of circulating near-infrared extinguishing nanoparticles,” J Biomed. Nanotechnol. 6(1), 73–81 (2010). [CrossRef] [PubMed]

18.

Y. Wang, X. Xie, X. Wang, G. Ku, K. L. Gill, D. P. O’Neal, G. Stoica, and L. V. Wang, “Photoacoustic tomography of a nanoshell contrast agent in the in vivo rat brain,” Nano Lett. 4(9), 1689–1692 (2004). [CrossRef]

19.

J. W. Severinghaus and Y. Honda, “History of blood gas analysis. VII. Pulse oximetry,” J. Clin. Monit. 3(2), 135–138 (1987). [CrossRef] [PubMed]

20.

J. G. Webster, Design of Pulse Oximeters , Chapter 4, pp. 40–55, New York, NY, Taylor and Francis Group, 1997.

21.

K. Yamakoshi and Y. Yamakoshi, “Pulse glucosimetry: a new approach for noninvasive blood glucose measurement using instantaneous differential near-infrared spectrophotometry,” J. Biomed. Opt. 11(5), 1–9 (2006). [CrossRef]

22.

T. Iijima, T. Aoyagi, Y. Iwao, J. Masuda, M. Fuse, N. Kobayashi, and H. Sankawa, “Cardiac output and circulating blood volume analysis by pulse dye-densitometry,” J. Clin. Monit. 13(2), 81–89 (1997). [CrossRef] [PubMed]

23.

T. Imai, C. Mitaka, T. Nosaka, A. Koike, S. Ohki, Y. Isa, and F. Kunimoto, “Accuracy and repeatability of blood volume measurement by pulse dye densitometry compared to the conventional method using 51Cr-labeled red blood cells,” Intensive Care Med. 26(9), 1343–1349 (2000). [CrossRef] [PubMed]

24.

N. Taguchi, S. Nakagawa, K. Miyasaka, M. Fuse, and T. Aoyagi, “Cardiac output measurement by pulse dye densitometry using three wavelengths,” Pediatr. Crit. Care Med. 5(4), 343–350 (2004). [CrossRef] [PubMed]

25.

Y. Mendelson, R. M. Lewinsky, and Y. Wasserman, “Multi-wavelength reflectance pulse oximetry,” Anesth. Analg. 94(1 Suppl), S26–S30 (2002). [PubMed]

26.

T. Aoyagi, M. Fuse, N. Kobayashi, K. Machida, and K. Miyasaka, “Multiwavelength pulse oximetry: theory for the future,” Anesth. Analg. 105(6 Suppl), S53–S58 (2007). [CrossRef] [PubMed]

27.

J. Kraitl, H. Ewald, and H. Gehring, “An optical device to measure blood components by a photoplethysmographic method,” J. Opt. A, Pure Appl. Opt. 7(6), S318–S324 (2005). [CrossRef]

28.

S. J. Barker, J. Curry, D. Redford, and S. Morgan, “Measurement of carboxyhemoglobin and methemoglobin by pulse oximetry: a human volunteer study,” Anesthesiology 105(5), 892–897 (2006). [CrossRef] [PubMed]

29.

W. G. Zijlstra, A. Buursma, and W. P. Meeuwsen-van der Roest, “Absorption spectra of human fetal and adult oxyhemoglobin, de-oxyhemoglobin, carboxyhemoglobin, and methemoglobin,” Clin. Chem. 37(9), 1633–1638 (1991). [PubMed]

30.

D. K. Sardar and L. B. Levy, “Optical properties of whole blood,” Lasers Med. Sci. 13(2), 106–111 (1998). [CrossRef]

31.

W. Cheong, S. A. Prahl, and A. J. Welch, “A review of the optical properties of biological tissues,” IEEE J. Quantum Electron. 26(12), 2166–2185 (1990). [CrossRef]

32.

D. J. Faber, M. C. G. Aalders, E. G. Mik, B. A. Hooper, M. J. C. van Gemert, and T. G. van Leeuwen, “Oxygen saturation-dependant absorption and scattering of blood,” Phys. Rev. Lett. 93(2), 1–4 (2004). [CrossRef]

33.

A. C. Guyton, and J. E. Hall, Textbook of Medical Physiology , Chapters 39–40, pp. 491–513, (Philadelphia, PA, Elsevier Saunders, 2006).

34.

S. A. Prahl, “Tabulated Molar Extinction Coefficients of Reduced and Oxygenated Hemoglobin,” http://omlc.ogi.edu/spectra/hemoglobin/summary.html (1998)

35.

A. J. Welch, and M. J. C. van Gemert, Optical-Thermal Response of Laser-Irradiated Tissue , New York, NY, Plenum Press, 1995.

36.

G. J. Michalak, “In vivo non-invasive monitoring of optically resonant metal nanoparticles using multi-wavelength photoplethysmography,” Dissertation published August 2010.

OCIS Codes
(170.1460) Medical optics and biotechnology : Blood gas monitoring
(170.1470) Medical optics and biotechnology : Blood or tissue constituent monitoring
(170.3890) Medical optics and biotechnology : Medical optics instrumentation
(350.4238) Other areas of optics : Nanophotonics and photonic crystals

ToC Category:
Medical Optics and Biotechnology

History
Original Manuscript: August 26, 2010
Revised Manuscript: November 9, 2010
Manuscript Accepted: November 18, 2010
Published: December 3, 2010

Citation
Gregory J. Michalak, Jon A. Schwartz, Glenn P. Goodrich, and D. Patrick O’Neal, "Three-wavelength murine photoplethysmography for estimation of vascular gold nanorod concentration," Opt. Express 18, 26535-26549 (2010)
http://www.opticsinfobase.org/oe/abstract.cfm?URI=oe-18-25-26535


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References

  1. S. Lal, S. E. Clare, and N. J. Halas, “Nanoshell-enabled photothermal cancer therapy: impending clinical impact,” Acc. Chem. Res. 41(12), 1842–1851 (2008). [CrossRef] [PubMed]
  2. M. P. Melancon, W. Lu, Z. Yang, R. Zhang, Z. Cheng, A. M. Elliot, J. Stafford, T. Olsen, J. Z. Zhang, and C. Li, “In vitro and in vivo targeting of hollow gold nanoshells directed at epidermal growth factor receptor for photo thermal therapy,” Mol. Cancer Ther. 7(6), 1730–1739 (2008). [CrossRef] [PubMed]
  3. C. Loo, A. Lowery, N. Halas, J. West, and R. Drezek, “Immunotargeted nanoshells for integrated cancer imaging and therapy,” Nano Lett. 5(4), 709–711 (2005). [CrossRef] [PubMed]
  4. A. M. Gobin, M. H. Lee, N. J. Halas, W. D. James, R. A. Drezek, and J. L. West, “Near-infrared resonant nanoshells for combined optical imaging and photothermal cancer therapy,” Nano Lett. 7(7), 1929–1934 (2007). [CrossRef] [PubMed]
  5. X. Huang, P. K. Jain, I. H. El-Sayed, and M. A. El-Sayed, “Plasmonic photothermal therapy (PPTT) using gold nanoparticles,” Lasers Med. Sci. 23(3), 217–228 (2008). [CrossRef]
  6. H. Liu, D. Chen, F. Tang, G. Du, L. Li, X. Meng, W. Liang, Y. Zhang, X. Teng, and Y. Li, “Photo thermal therapy of Lewis lung carcinoma in mice using gold nanoshells on carboxylated polystyrene spheres,” Nanotechnology 19(34), 1–7 (2008). [CrossRef]
  7. D. P. O’Neal, L. R. Hirsch, N. J. Halas, J. D. Payne, and J. L. West, “Photo-thermal tumor ablation in mice using near infrared-absorbing nanoparticles,” Cancer Lett. 209(2), 171–176 (2004). [CrossRef] [PubMed]
  8. J. H. Park, G. von Maltzahn, M. J. Xu, V. Fogal, V. R. Kotamraju, E. Ruoslahti, S. N. Bhatia, and M. J. Sailor, “Cooperative nanomaterial system to sensitize, target, and treat tumors,” Proc. Natl. Acad. Sci. U.S.A. 107(3), 981–986 (2010). [CrossRef] [PubMed]
  9. H. Wang, T. B. Huff, D. A. Zweifel, W. He, P. S. Low, A. Wei, and J. X. Cheng, “In vitro and in vivo two-photon luminescence imaging of single gold nanorods,” Proc. Natl. Acad. Sci. U.S.A. 102(44), 15752–15756 (2005). [CrossRef] [PubMed]
  10. T. Niidome, M. Yamagata, Y. Okamoto, Y. Akiyama, H. Takahashi, T. Kawano, Y. Katayama, and Y. Niidome, “PEG-modified gold nanorods with a stealth character for in vivo applications,” J. Control. Release 114(3), 343–347 (2006). [CrossRef] [PubMed]
  11. Y. Akiyama, T. Mori, Y. Katayama, and T. Niidome, “The effects of PEG grafting level and injection dose on gold nanorod biodistribution in the tumor-bearing mice,” J. Control. Release 139(1), 81–84 (2009). [CrossRef] [PubMed]
  12. W. D. James, L. R. Hirsch, J. L. West, P. D. O’Neal, and J. D. Payne, “Application of INAA to the build-up and clearance of gold nanoshells in clinical studies in mice,” J. Radioanal. Nucl. Chem. 271(2), 455–459 (2007). [CrossRef]
  13. H. Xie, K. L. Gill-Sharp, and D. P. O’Neal, “Quantitative estimation of gold nanoshell concentrations in whole blood using dynamic light scattering,” Nanomedicine 3(1), 89–94 (2007). [CrossRef] [PubMed]
  14. R. T. Zaman, P. Diagaradjane, J. C. Wang, J. Schwartz, N. Rajaram, K. L. Gill-Sharp, S. H. Cho, H. G. Rylander, J. D. Payne, S. Krishnan, and J. W. Tunnell, “In vivo detection of gold nanoshells in tumors using diffuse optical spectroscopy,” IEEE. J. Sel. Top. Quant. Electron. 13, 1715–1720 (2007). [CrossRef]
  15. T. Niidome, Y. Akiyama, K. Shimoda, T. Kawano, T. Mori, Y. Katayama, and Y. Niidome, “In vivo monitoring of intravenously injected gold nanorods using near-infrared light,” Small 4(7), 1001–1007 (2008). [CrossRef] [PubMed]
  16. G. J. Michalak, G. P. Goodrich, J. A. Schwartz, W. D. James, and D. P. O’Neal, “Murine photoplethysmography for in vivo estimation of vascular gold nanoshell concentration,” J. Biomed. Opt. 15(4), 047007 (2010). [CrossRef] [PubMed]
  17. G. J. Michalak, H. A. Anderson, and D. P. O’Neal, “Feasibility of using a two-wavelength photometer to estimate the concentration of circulating near-infrared extinguishing nanoparticles,” J Biomed. Nanotechnol. 6(1), 73–81 (2010). [CrossRef] [PubMed]
  18. Y. Wang, X. Xie, X. Wang, G. Ku, K. L. Gill, D. P. O’Neal, G. Stoica, and L. V. Wang, “Photoacoustic tomography of a nanoshell contrast agent in the in vivo rat brain,” Nano Lett. 4(9), 1689–1692 (2004). [CrossRef]
  19. J. W. Severinghaus and Y. Honda, “History of blood gas analysis. VII. Pulse oximetry,” J. Clin. Monit. 3(2), 135–138 (1987). [CrossRef] [PubMed]
  20. J. G. Webster, Design of Pulse Oximeters, Chapter 4, pp. 40–55, New York, NY, Taylor and Francis Group, 1997.
  21. K. Yamakoshi and Y. Yamakoshi, “Pulse glucosimetry: a new approach for noninvasive blood glucose measurement using instantaneous differential near-infrared spectrophotometry,” J. Biomed. Opt. 11(5), 1–9 (2006). [CrossRef]
  22. T. Iijima, T. Aoyagi, Y. Iwao, J. Masuda, M. Fuse, N. Kobayashi, and H. Sankawa, “Cardiac output and circulating blood volume analysis by pulse dye-densitometry,” J. Clin. Monit. 13(2), 81–89 (1997). [CrossRef] [PubMed]
  23. T. Imai, C. Mitaka, T. Nosaka, A. Koike, S. Ohki, Y. Isa, and F. Kunimoto, “Accuracy and repeatability of blood volume measurement by pulse dye densitometry compared to the conventional method using 51Cr-labeled red blood cells,” Intensive Care Med. 26(9), 1343–1349 (2000). [CrossRef] [PubMed]
  24. N. Taguchi, S. Nakagawa, K. Miyasaka, M. Fuse, and T. Aoyagi, “Cardiac output measurement by pulse dye densitometry using three wavelengths,” Pediatr. Crit. Care Med. 5(4), 343–350 (2004). [CrossRef] [PubMed]
  25. Y. Mendelson, R. M. Lewinsky, and Y. Wasserman, “Multi-wavelength reflectance pulse oximetry,” Anesth. Analg. 94(1Suppl), S26–S30 (2002). [PubMed]
  26. T. Aoyagi, M. Fuse, N. Kobayashi, K. Machida, and K. Miyasaka, “Multiwavelength pulse oximetry: theory for the future,” Anesth. Analg. 105(6Suppl), S53–S58 (2007). [CrossRef] [PubMed]
  27. J. Kraitl, H. Ewald, and H. Gehring, “An optical device to measure blood components by a photoplethysmographic method,” J. Opt. A, Pure Appl. Opt. 7(6), S318–S324 (2005). [CrossRef]
  28. S. J. Barker, J. Curry, D. Redford, and S. Morgan, “Measurement of carboxyhemoglobin and methemoglobin by pulse oximetry: a human volunteer study,” Anesthesiology 105(5), 892–897 (2006). [CrossRef] [PubMed]
  29. W. G. Zijlstra, A. Buursma, and W. P. Meeuwsen-van der Roest, “Absorption spectra of human fetal and adult oxyhemoglobin, de-oxyhemoglobin, carboxyhemoglobin, and methemoglobin,” Clin. Chem. 37(9), 1633–1638 (1991). [PubMed]
  30. D. K. Sardar and L. B. Levy, “Optical properties of whole blood,” Lasers Med. Sci. 13(2), 106–111 (1998). [CrossRef]
  31. W. Cheong, S. A. Prahl, and A. J. Welch, “A review of the optical properties of biological tissues,” IEEE J. Quantum Electron. 26(12), 2166–2185 (1990). [CrossRef]
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